Comment by ramesh31
11 hours ago
Everyone wants to come up with a clever One Spec to Rule Them All for generative UI. My bet is that the bitter lesson still bites. Models will continue getting faster and more error free at single-shot writing things from scratch with primitive libraries, and the flexibility that allows will make all of this for naught.
So this is a fairly domain specific (dashboards) spec and we intentionally avoid getting too generic.
The raw HTML/SVG or base libraries approach may well win out, but it does make it quite hard or impossible for humans to follow along and verify for instance where the numbers on a chart came from.
I think in a future where AI's doing all that verifying (or we just trust it), the AI might still prefer to use a DSL like ours because the abstraction maintains consistency, lowers maintenance, and saves a lot of tokens.
But the most helpful bits of a structured DSL are for sure still for humans. The structured format ensures things are readable and testable. Ours also enables a generative UI, which for now at least is still a much faster way to make visual edits while working with an AI, vs always through it.
I think we're still ways out until companies will blindly trust AI that the data they pulled is correct. If a data team member sees a dashboard or chart, their first questions is "Is the SQL below this chart correct?". The easier it is to see the SQL that pulled the data, the better.
Exactly and that's why dbt Charts is a spec in YAML vs a python library. It ensures that the logic stays in SQL where its easy to test and trace.